Sand monitoring within wells using acoustic arrays

ABSTRACT

A method for detecting the presence of particles, such as sand, flowing within a fluid in a conduit is disclosed. At least two optical sensors measure pressure variations propagating through the fluid. These pressure variations are caused by acoustic noise generated by typical background noises of the well production environment and from sand particles flowing within the fluid. If the acoustics are sufficiently energetic with respect to other disturbances, the signals provided by the sensors will form an acoustic ridge on a kω plot, where each data point represents the power of the acoustic wave corresponding to that particular wave number and temporal frequency. A sand metric then compares the average power of the data points forming the acoustic ridge to the average power of the data points falling outside of the acoustic ridge. The result of this comparison allows one to determine whether particles are present within the fluid. Furthermore, the present invention can also determine whether the generated acoustic noise is occurring upstream or downstream of the sensors, thus giving an indication of the location of the particles in the fluid relative to the sensors.

FIELD OF THE INVENTION

[0001] This invention relates generally to fluid sensing, and moreparticularly to detecting particles flowing in a fluid within a conduit.

BACKGROUND OF THE INVENTION

[0002] The production of particles, such as sand, concerns operators ofoil/gas wells because of the possible catastrophic consequences onproduction. (In this disclosure, “sand should be understood as referringto solid particulate matter as would be found in an oil/gas well,without particular regard to its size or diameter). The production ofsand may start at relatively minor levels, but then may rapidly increaseresulting in clogged well lines that effectively “fill in” the well andhalt production. Sand can also contaminate the separator tanks, whichtypically connect to other producing wells. When this occurs, theproduction of all oil wells feeding into the separator tanks must behalted. Furthermore, once sand has entered into the completionequipment, corrosion and/or erosion is likely, resulting in significanteconomic loss.

[0003] Operators will thus labor to avoid the production of sandcompletely, or at least attempt to detect sand at minor levels so thatevasive action can be taken. By detecting sand at minor levels theoperator may, for example, lower the rate of production (which mightallow the sand to fall back through the well), reduce or ceasecompletely any water injection, or in a multiple well system, shut downthe affected well completely while allowing the other wells to continueproduction. In short, the onset of sand production is often the limitingfactor in maximizing the production for a given oil and gas well.Because of the serious consequences associated with unnoticed sandproduction as described above, operators apply conservative productionlimits, which reduce the maximum production rates. Thus, a largeincentive exists in the industry for methods of detecting sand quicklyand continuously.

[0004] A variety of methods currently exist in the oil and gas industryto detect sand production. One such method is to physically filter asample of produced fluids to check for solid particles. One problem withthis method is that by the time the fluid has risen to the top of thewell, it may be too late as contamination of the separator tanks andcompletion equipment may have already occurred. Furthermore, thefiltering of selected samples will not detect sand continuously butinstead only at designated time intervals. Therefore, this method isunlikely to detect sand at the inception of production when sand maymost likely be encountered.

[0005] A technique that continuously monitors for sand production sensesthe vibrations caused by sand impacting the pipe or conduit in which thesand flows. These devices, such as a ClampOn™ meter, clamp on to thepipe, typically at an “elbow” or section of the pipe where the fluid hasto take an abrupt turn, and use ultrasonic detection methods to listenfor the impact vibration of the sand. However, these ultrasonic methodstypically only provide a qualitative measurement and are plagued withthe difficulties associated with ultra high frequency coupling into thepipe. Furthermore, the device must be located near an elbow, thus wouldbe unsuitable in the straight or slightly bend piping networks downhole.Although they have the benefit of continuous monitoring, they may alsodetect the presence of sand too late as they are practically limited tothe surface environment.

[0006] Real-time monitoring of sand production would be valuableanywhere in the production string, but is particularly valuabledownhole, i.e., in conjunction with the production tube, where sandwould initially be produced before flowing to the surface. With theemergence of fiber optic sensors, continuous monitoring of fluids in thedownhole environment is possible. Fiber optic sensors and flowmetersalready monitor parameters such as fluid sound speed, fluid velocity,pressure, and temperature. Such fiber optic based flowmeters aredisclosed in the following U.S. Patent Applications and Patents, and arehereby incorporated by reference in their entireties: Ser. No.09/740,760, entitled “Apparatus for Sensing Fluid in a Pipe,” filed Nov.29, 2000; Ser. No. 10/115,727, entitled “Flow Rate Measurements UsingUnsteady Pressures,” filed Apr. 3, 2002; and U.S. Pat. No. 6,354,147,entitled “Fluid Parameter Measurement in Pipes Using AcousticPressures,” issued Mar. 12, 2002 [hereinafter referred to as the “flowmeter references.”]. The ability to reliably monitor sand productiondownhole in real-time, as the above parameters are currently measured,would allow for more effective management of sand production problems.Furthermore, coupling this capability with the real-time measurement ofthese other parameters results in a powerful fiber optic flowmeter formanaging and optimizing well productivity.

[0007] The art would therefore benefit from a sensor that can be placedat any location along the production pipe and that can detect sandparticles at minimal levels, thus allowing the operator to respond in anappropriate and timely manner to the production of sand.

SUMMARY OF THE INVENTION

[0008] A method for detecting the presence of particles, such as sand,flowing within a fluid in a conduit is disclosed. At least two opticalsensors measure pressure variations propagating through the fluid. Thesepressure variations are caused by acoustic noise generated by typicalbackground noises of the well production environment and from sandparticles flowing within the fluid. If the acoustics are sufficientlyenergetic with respect to other disturbances, the signals provided bythe sensors will form an acoustic ridge on a kω plot, where each datapoint represents the power of the acoustic wave corresponding to thatparticular wave number and temporal frequency. A sand metric thencompares the average power of the data points forming the acoustic ridgeto the average power of the data points falling outside of the acousticridge. The result of this comparison allows one to determine whetherparticles are present within the fluid. Furthermore, the presentinvention can also determine whether the generated acoustic noise isoccurring upstream or downstream of the sensors, thus giving anindication of the location of the particles in the fluid relative to thesensors.

BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The foregoing and other features and aspects of the presentdisclosure will be best understood with reference to the followingdetailed description of embodiments of the invention, when read inconjunction with the accompanying drawings, wherein:

[0010]FIG. 1 illustrates a system for detecting the presence ofparticles in a fluid, according to the present invention.

[0011]FIG. 2 illustrates a kω plot with an acoustic ridge occurringabove and below the meter, according to the present invention.

[0012]FIG. 3 illustrates a graph of power versus velocity with a peakcorresponding to the fluid sound speed, according to the presentinvention.

[0013]FIG. 4 illustrates kω plots suspected of indicating the presenceof sand falling through a well whose production has been halted.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

[0014] In the disclosure that follows, in the interest of clarity, notall features of actual implementations are described in this disclosure.It will of course be appreciated that in the development of any suchactual implementation, as in any such project, numerous engineering anddesign decisions must be made to achieve the developers' specific goals,e.g., compliance with mechanical and business related constraints, whichwill vary from one implementation to another. While attention mustnecessarily be paid to proper engineering and design practices for theenvironment in question, it should be appreciated that the developmentof a method to detect particles, such as sand, flowing within a conduitwould nevertheless be a routine undertaking for those of skill in theart given the details provided by this disclosure, even if suchdevelopment efforts are complex and time-consuming.

[0015] The present invention preferably uses a phased spatial array ofoptical sensors with Bragg gratings that measure acoustic pressure wavescaused by sand particles propagating through the fluid. The sensors maymeasure the acoustic pressure waves by techniques disclosed in U.S. Pat.No. 6,354,147 entitled, “Fluid Parameter Measurement In Pipes UsingAcoustic Pressures,” or by sonar processing techniques disclosed in U.S.patent application, Ser. No. 09/997,221 entitled, “Method And System ForDetermining The Speed Of Sound In A Fluid Within A Conduit,” filed Nov.28, 2001, both of which are incorporated herein by reference in theirentirety. Furthermore, the optical sensors may comprise the acousticsensing arrays found in the incorporated “flow meter references” listedabove. By analyzing the power of the signals provided by the opticalsensors through the use of a “sand metric,” the present inventionenables one to determine the presence of particles, such as sand, withinthe fluid.

[0016] Acoustic “background” noise is present within the fluid flowingwithin the production pipe. Such acoustics arise from a variety ofsources, and can be useful in the detection of parameters of the fluid.For example, as disclosed in the incorporated “flow meter references,”the naturally occurring pressure perturbations in the flowing fluid orfluid mixture can be used to determine, for example, the speed of sound,velocity, and other parameters of the fluid as previously mentioned.However, it has also been found that particles flowing within a fluidgenerate sufficient acoustic noise detectable over these other, morenormal noises occurring within the fluid. Therefore, by analyzing thepower of the acoustic signals, as will be discussed in more detailbelow, and by comparing that power with the power generated by otherbackground noises, the presence of particles may be detected. A varietyof interactions between the sand particles in a fluid cause thisdetectable acoustic noise, which occurs generally within the range of100 Hz to 6,000 Hz, and more specifically, within the range of 200 Hz to800 Hz. Mechanisms causing particle acoustic noise may include: (1)noise generated from the increased turbulence resulting from the fluidflowing over the multitude of particles, and (2) impact and scraping ofthe particles along the walls of the conduit.

[0017] Referring now to FIG. 1, a system according to the presentinvention for detecting particles in a fluid 11 flowing within a conduit13 is shown. An array of pressure sensors 14, 16, 18 provide signals 20,22, 24 indicative of the fluid pressure at each sensor location at anumber of successive instants of time. (More sensors, or two sensors,could also be used). The array of sensors 14, 16, 18 measure theunsteady pressure disturbances within the fluid 11 caused by sand andother phenomenon propagating with or within the fluid. The sensors 14,16, 18 may comprise fiber optic sensors and may further comprise anynumber of sensors equal to two or greater. The fiber optic sensors maycoil around the conduit 13 in a series of wraps. As is disclosed in theabove-incorporated “flow meter references,” each wrap may be separatedby a single Bragg grating for time division multiplexing (TDM) or eachwrap may be separated by a pair of Bragg gratings for wavelengthdivision multiplexing (WDM). However, other types of pressure sensors,such as electrical or mechanical sensors, could be used with the presentdisclosure, again as disclosed in the “flow meter references.”

[0018] As noted, the sensors 14, 16, 18 produce time varying pressure(Px_(i)(t)) signals indicative of the pressure of the acousticdisturbance detected at each of the sensors, in effect renderinginformation about pressure as a function of both location (x) and time(t), i.e., P(x,t). In a preferred embodiment useful in the detection ofsand, these pressure signals are converted at processor 26 usingwell-known techniques into a kω plot where k is wavenumber (2π/λ), and ωis the angular frequency (2πf). This conversion is affected at theprocessor 26 and preferably involves the use of well-known FourierTransform algorithms. However, other spatial/temporal conversions (e.g.,the generation of an xω plot, a kt plot, etc.) are also possible anduseful with the disclosed technique, and “kω plot” should be understoodas including these other types of spatial/temporal conversions. Becausetwo variables (x and t) are transformed into two different variables (ωand k), a two-dimensional transform is utilized as one skilled in theart will understand. The well-known CAPON method, the MUSIC method,deterministic maximum likelihood methods, the minimum variancedistortionless response method (MVDR) or MVDR beamformer methods, orother beamforming methods, are all preferred two-dimensional transformsuseful in the present disclosure. The details of this conversion, thephysics of wave propagation inside a pipe containing a fluid, and otherconsiderations relevant to this technique, are disclosed inpreviously-incorporated U.S. patent application Ser. No. 09/997,221, andare not repeated here for simplicity.

[0019]FIG. 2 shows an exemplary kω plot to be analyzed pursuant to thedisclosed technique. The vertical axis of the plot is the temporal orangular frequency (ω) of the signal in rad/s and the horizontal axis isthe spatial frequency or wave number (k) (e.g., in 1/ft). Each point(i.e., frequency) in the plot has associated with it a power level (indB), as denoted by regions 100 a-100 d. In this regard, and in thecomputerized environment in which the kω plot is generated, it should beunderstood that the kω plot constitutes a data set in which each pixelcomprises a particular power value, and not necessarily a visual plot.

[0020] Several different determinations about system acoustics can bemade using the kω plot. First, it should be noticed that theaccumulation of all of the acoustic events represented in the plot liegenerally along straight lines, referred to as a “ridge” 430. Thisreflects the fact that all of the detected various acoustic events, eachhaving its own unique frequency constitutions, travel through the fluidat approximately the same speed through the fluid, i.e., the fluid speedof sound. This fluid speed of sound, c, can therefore be calculated bycomputing a best fit line(s) 410, 420 within the ridge(s), anddetermining that line's slope, where ω=ck. (Dispersion, whereby thespeed of sound in the fluid changes as a function of the frequency beingtransmitted, would cause this slope to deviate from linear, butsignificant dispersion should not occur with the frequencies of interestin a traditional oil/gas multiphase flow measurement, which ranges fromapproximately 10 Hz to approximately 2000 Hz). In short, the speed ofsound in the fluid, c, can be calculated by using a kω plot, which canbe useful in determining important parameters concerning the fluid beingmeasured, such as its density or its phase fractions, as is noted inincorporated Pat. No.6,354,147. (As noted in that patent and in theincorporated 09/997,221 application, pipe compliancy may need to becorrected for to determine the speed of sound in the fluid in anunbounded media, which might be a more useful parameter for certainapplications). In an actual kω plot, a vertical ridge will also beapparent, but this is an artifact of various system noise and is notsignificant to determining the presence of sand or other systemparameters. Hence, this vertical ridge is not shown in either FIG. 2 orFIG. 4 for clarity.

[0021] Second, and as shown in FIG. 2, the power of the various acousticphenomena that are represented in the kω plot can be determined.Accordingly, regions 100 a-100 d represent areas of differing powerlevels, in which region 100 d represents the highest power levels (e.g.,20 db), region 100 c represents lower power levels (e.g., 10 db), etc.As one skilled in the art will understand, these power regions may bemore uneven or blotchy in shape, and FIG. 2 shows only an idealizedrepresentation of the reflected power levels. As described below, anassessment of the power levels within a certain frequency range on thekω plot assists in determining the presence of sand.

[0022] Third, the kω plot allows for directionality of the acousticaldisturbances to be determined. Referring to FIG. 1, the measuredacoustics can arrive at the sensor array 110 as either lefttraveling-waves or right traveling waves, corresponding to energy on theleft side or the right side of the kω plot. Because the speed of thefluid flowing within the pipe is usually much smaller than the speed ofsound in the fluid, these left-traveling or right-traveling acousticdisturbances will approach the array 110 at approximately the same speed(assuming that the Mach number of the flow is <<1). Left-travelingdisturbances will correspond to negative k values, while right-travelingdisturbances correspond to positive k values. Thus, assuming thatacoustics are being generated from both the left and the right of thearray 110, as they would in when the fluid is flowing and acousticaldisturbances are being created by sand and other natural phenomena inthe fluid, the kω plot will exhibit two ridges 430, one along line 410,which is indicative of left traveling acoustics, and another along line420, which is indicative of right traveling acoustics. Because theleft-traveling and right-traveling waves arrive at approximately thesame speed as mentioned above, the absolute value of the slopes of bothlines 410, and 420 will be approximately equal, and both indicative ofthe speed of sound in the fluid.

[0023] The ridges 430 in the kω plot are assessed in the system by acomputerized ridge identifier 27, as shown in FIG. 1, which can identifythe ridges 430 using many known computerized techniques for assessingplots or plot data files. For example, the ridge identifier 27 can bepreprogrammed with a power level threshold, in which pixels in the plothaving values exceeding this threshold are deemed to constitute aportion of the ridge 430. Once the area of the plot containing the ridge430 has been identified, its slope (i.e., lines 410 and 420) can bedetermined by analyzer 28, which preferably employs a weighted leastsquares fitting algorithms or other fitting algorithm well known in theart.

[0024] Referring still to FIG. 1, care should be taken to position thesensors 14, 16, 18 with suitable spacing (preferably, equally spaced byΔX) for the application at hand to detect acoustical frequencies ofinterest. Of course, any particular acoustical phenomenon, such as thosecaused by sand, will comprise a plurality of frequency components. If asingle frequency component is considered, the disclosed system obtainsinformation about the wavelength λ (or the wavenumber k) of thatfrequency component essentially by sensing the phase of that componentat (at least) any two of the sensors 14, 16, 18. Thus, the separation ΔXcan be determined to be a particular fraction of a wavelength of thesound to be measured. The information is only not ambiguous, however, ifthe sensors sample frequently enough to avoid temporal aliasing, and areclose enough to avoid spatial aliasing. For example, if the sensors area distance ΔX apart that is two wavelengths of the frequency componentbeing measured, the system may incorrectly indicate a value for thewavelength that is twice the actual value. Taking these practicallimitations into account, it is preferred that the sensor 14, 16, and 18be spaced at a distance ΔX of approximately eighteen inches apart,center to center, such as disclosed in the incorporated reference Ser.No. 09/740,760. Should it be necessary to resolve frequencies over alarger range than a single spacing distance would permit, additionalsensors spaced at appropriate intervals could be added.

[0025] Sand creates acoustic phenomenon in the fluid which as notedtravels at the speed of sound in the fluid, as do the other phenomenathat are present or naturally occurring in the fluid. Accordingly, theacoustic phenomenon produced by the sand will lie along the same ridge430 to which these other phenomena contribute. However, the presence ofsand adds additional power to the acoustics in the fluid, and evidencesuggests that it adds that power within a certain frequency range, e.g.,between 200 to 800 Hz. Accordingly, by assessing either or both of theseeffects, the presence of sand can be inferred. Moreover, and asfacilitated by the use of fiber optic based flow meters, such detectioncan be performed continuously directly at the production pipe beforesand reaches the top of the well.

[0026] As just noted, the presence of sand will add extra acousticenergy to the fluid flowing inside the pipe. Quantification of thisenergy, in one embodiment of the present invention, is performed bycomputation at analyzer 28 of a “sand metric” M that can be used todetect the presence of sand or to quantify the amount of sand present.In one embodiment, the sand metric computes the ratio of the averageacoustical power along the ridge, P_(acoustics), divided by the averageacoustical power of some range outside of the ridge, P_(non-acoustics).To normalize this embodiment of the sand metric, this ratio issubtracted by one so that the metric equals zero when no ridge ispresent, and is greater than zero when a ridge is present, i.e.:$M = {\frac{P_{acoustics}}{P_{{non} - {acoustics}}} - 1}$

[0027] As one skilled in the art will realize, there are various ways bywhich the analyzer 28 can compute the power values to be used in thesand metric, and either average power values or summed power values maybe used. In one embodiment, and referring again to FIG. 2, a straightline 500 passing through the origin at k=0 can be swept through a rangeof sound speeds (i.e., slopes) and the power of the various pixels inthe kω plot can be summed (or averaged) along that line 500. Whencomputing these summed or averaged powers, it is preferable to limit theanalysis to frequencies where the acoustics generated from sand arelikely to be found, such as from 200 Hz to 800 Hz, but may include otherfrequencies as well. Frequencies above and below this threshold rangeare preferably discounted.

[0028]FIG. 3 shows the results of this analysis for a sound speed rangeof 2,000 to 10,000 ft/sec. As expected, this graphs yields a powermaximum 570 corresponding to the speed of sound in the fluid beinganalyzed for sand content, i.e., along line 420 of FIG. 2. (A similaranalysis can be performed along line 410 as well). With this maximumlocated, the analyzer 28 can use various criteria to determine whichspeeds of sound correspond to the ridge (i.e., P_(acoustics)) and whichfall outside that range (i.e., P_(non-acoustics)). For example, themaximum and minimum speeds of sound corresponding to power within theridge, 520 and 510, may be defined as the full-width-half-maximum (FWHM)of the maximum 570, and may be defined according to set power levels(e.g., 30% of the maximum), or may be defined as a set range around themaximum. Likewise, the ranges 535 and 555 corresponding to the regionsoutside of the ridge, may be defined by limits 540 and 550 which aresimilarly related to the maximum, or which correspond to minimum powervalues, etc. After these limits are set, the values P_(acoustics) andP_(non-acoustics) can be calculated by summing or averaging the powervalues within these defined ranges. Of course, one skilled in the artwill recognize that calculation of these power values for the sandmetric can be calculated in any number of ways.

[0029] Once P_(acoustic) and P_(non-acoustic) and the sand metric M arecalculated, the metric can be correlated to the presence of sand in anynumber of ways. In this regard, it is useful to remember that phenomenaother than sand can contribute to the energy present at the ridge on thekω plot. Therefore, experimentation with or calibration of the pipesystem being monitored may be necessary to understand when the sandmetric is indicating the presence or quantity of sand. For example,suppose that an array deployed in operation consistently yields a sandmetric of 10. If this value is seen to increase to a value of 12, and ifdetection of other parameters in the system cannot explain the increaseacoustic energy, it may be inferred or at least contemplated that sandis being produced. Further verification of the presence of sand can thenbe performed, including techniques again employing the use of a kω plotas will be explained shortly. Correlation of the sand metric with otherknown sand detection techniques can also help to verify that theincrease in the sand metric in fact correlates to sand production. Forexample, the flow meter before deployment can be calibrated using testequipment, such as a flow loop, and sand metric values can be calculatedwhen the system is sand-filled or sand-free. Correlating the sandcontents of sampled production fluids with the sand metric can furtherassist in determining normal values or ranges for the sand metric whichwould correlate to the production of sand. Other equations may be usedto provide a sand metric that compares the ridge power to non-ridgebased power, and the equation listed above should only be understood asexemplary.

[0030] It has proven difficult to test the utility of the disclosedapparatus and method to detect sand in a test flow loop, as the noiseinvolved in a flow loop test apparatus has been seen to overwhelm theacoustics of sand introduced into the loop. However, data suggestive ofthe utility of the disclosed embodiments to detect sand is evidenced byan experiment which was performed on an actual working test well. Inthis test, a fiber optic based flow meter such as that incorporatedherein was placed onto a production tube and lowered approximately22,000 feet into a well suspected of producing sand. The well wasactivated to pump produced fluids to the surface. Production was thenstopped, but the flow meter continued operation to monitor the acousticswithin the production pipe.

[0031]FIG. 4 illustrates the kω plots that were acquired at varioustimes after production was halted. (The kω plots in FIG. 4, whileindicative of actual data, are only exemplary, and have been simplifiedfor illustration purposes). At the first test point 1 (time=0), nomeasurable acoustics were seen. Thereafter, at test point 2 (time=22minutes later), a ridge appeared only on the right side of plot, whichindicates that acoustics were being generated from some source above butnot below the flow meter. The “top based” acoustics were seen toincrease in power at test point 3 (time=31 minutes). At test point 4(time=39 minutes), the acoustics were seen both above and below the flowmeter. At test point 5 (time=43 minutes), the acoustics moved solelybelow the meter, and at test point 6 (time=61 minutes) the power ofthese “bottom based” acoustics dropped off to lower levels. At testpoint 7 (time=78 minutes), no appreciable acoustics were recorded.

[0032] It is theorized that the results seen in FIG. 4 are indicative ofthe presence of sand. Specifically, it is believed that a slug of sandwas produced and was present near the top of the well after productionwas halted. Initially, the acoustics generated by this produced sandwere not seen (test point 1) because they were too remotely located fromthe meter, and hence the sound generated by the sand was too attenuatedby the time it reached the meter. However, as the sand fell back intothe well due to gravity, it eventually approached the meter (test point2), and the acoustical power generated by this sand increased as thesand came closer to the flow meter (test point 3). At test point 4, itis theorized that the falling sand had approached the meter, and to someextent exceeded past the meter as acoustics were now seen both above andbelow the flow meter. As the sand continued to fall past the meter, thepower was seen only below the meter (test point 5), with decreasingpower levels (test point 6), until the sand became too far away from themeter for its acoustics to be resolvable (test point 7).

[0033] It is hypothesized that the settling of produced sand could bethe only cause of these results. Accordingly, the disclosed techniqueoffers additional advantages for the detection of sand. If produced sandis suspected or detected while the well is producing, either using thedisclosed sand metric or by other techniques, production can betemporarily halted to see if sand falls past the meter, i.e., if “topbased” acoustics are seen followed by “bottom based” acoustics.Alternatively or in addition, the “top based” acoustics could beassessed to see if they increase in power over time, or the “bottombased” acoustics could be asses to see if they decrease in power overtime. Although this constitutes an undesirable brief interruption inproduction, the interruption is only temporary, and would be worth thedelay if the presence of sand can be verified, which might allowproduction to be varied to reduce the possibility of the continuedproduction of sand. In short, the disclosed apparatus and techniques fordetecting the presence of sand has utility both when the well isoperational and fluid is flowing, and when production has been halted.If multiple meters are arrayed (e.g., multiplexed in series) along theproduction pipe, this method of determining the presence of sand can beredundantly verified, as the operator can listen for sand falling pastthe first meter, then the second meter, and so on.

[0034] The above-referenced test relies on the force of gravity to pullsand downward into the well, wherein the falling sand creates acousticdisturbances that are detectable by the flow meter. Accordingly, thedetection technique that this test illustrates will perform best onwells or conduits that are vertical, although this is not strictlynecessary.

[0035] “Directionally detecting” the acoustic disturbances in the fluidthat are caused by sand should be understood as not merely determiningthe mere presence of acoustic disturbances. Instead, this phrase shouldbe understood as meaning not only that acoustic are detected, but thattheir source is understood with relation to the flow meter that detectsthe disturbances, i.e., as either above or below the meter. As notedherein, the ability of the disclosed apparatus and methods to employdirectional detection of acoustic phenomenon allows added flexibilityover prior art approaches to fluid acoustic detection that merelydetects acoustics without knowledge of its source.

[0036] Furthermore, kω based processing applies temporal and spatialfiltering techniques to increase the effective signal-to-noise ratio ofsand generated acoustics, i.e., the disclosed method only considers theincrease of acoustics propagating at the speed of sound of the fluidover a specific frequency range. Other signals with the sensor outputsuch as electrical noise, vortical noise, impact noise propagatingwithin the production tubing, are all effectively filtered out by thedisclosed method.

[0037] It is contemplated that various substitutions, alterations,and/or modifications, including but not limited to those designalternatives which might have been specifically noted in thisdisclosure, may be made to the disclosed embodiment without departingfrom the spirit and scope of the invention as defined in the appendedclaims. For example, while particularly useful in detecting sand withina production pipe of an oil/gas well, the disclosed apparatus and methodwill have utility with respect to the detection of particulates in anypipe and in other industrial environments.

What is claimed is:
 1. A method for detecting particles in a fluidwithin a conduit, comprising: placing at least two sensors along theconduit; measuring acoustic disturbances within the fluid using thesensors to produce at least two pressure signals; and converting thepressure signals to form a data set indicative of the power of thepressure disturbances; computing a metric indicative of the presence ofparticles in the fluid using the data set.
 2. The method of claim 1,wherein the pressure signals are indicative of distance and time.
 3. Themethod of claim 1, wherein the data set is indicative of the frequencyand wavelength of the acoustic disturbances.
 4. The method of claim 3,wherein the frequencies within the data set are filter prior tocomputing the metric.
 5. The method of claim 4, wherein the filterfrequencies occur within the range of approximately 200 to 800 Hz. 6.The method of claim 1, wherein the metric comprises an assessment of thepower traveling at the speed of sound in the fluid.
 7. The method ofclaim 1, wherein the metric further comprises an assessment of the powertraveling at the speed of sound in the fluid and the power not travelingat the speed of sound in the fluid.
 8. The method of claim 1, whereinthe data set comprises a kω plot.
 9. The method of claim 8, whereincomputing the metric comprises identifying a ridge in the kω plot,wherein the ridge corresponds to the acoustic disturbances that aretraveling at the speed of sound in the fluid.
 10. The method of claim 9,wherein computing the metric comprises computing an averaged or summedpower along the ridge.
 11. The method of claim 10, wherein computing themetric further comprises computing an averaged or summed power in aregion outside of the ridge.
 12. The method of claim 11, wherein theregion outside of the ridge corresponds to a range of speeds of sound inthe fluid.
 13. The method of claim 11, wherein the metric comprises acalculation containing as variables (i) the averaged or summed poweralong the ridge, and (ii) the averaged or summed power in the regionoutside of the ridge.
 14. The method of claim 1, wherein the sensors arecoupled to an exterior surface of the conduit.
 15. The method of claim1, wherein the sensors are wrapped around the conduit.
 16. The method ofclaim 15, wherein the sensors comprise fiber optic cable.
 17. The methodof claim 16, wherein the sensors each comprise at least one wrap offiber optic cable.
 18. The method of claim 17, wherein the sensors areserially coupled to fiber Bragg gratings.
 19. A method for detectingparticles in a fluid within a conduit using a flow meter coupled to theconduit, comprising in order: (a) ceasing the flow of fluid through theconduit; (b) directionally detecting acoustic disturbances within thefluid above the meter at a first time; and (c) directionally detectingacoustic disturbances within the fluid below the meter at a second time.20. The method of claim 19, wherein directionally detecting the acousticdisturbances comprises the use of a kω data set.
 21. The method of claim20, wherein step (b) comprises assessing the data set for a single ridgeand wherein step (c) comprises assessing the data set for a singlesecond ridge different from the first ridge.
 22. The method of claim 21,wherein the acoustic disturbances lie along the first or second ridge.23. The method of claim 19, wherein the acoustic disturbances travel atthe speed of sound in the fluid.
 24. The method of claim 19, wherein theflow meter comprises at least two sensors.
 25. The method of claim 24,wherein the sensors are coupled to the outside of the conduit.
 26. Themethod of claim 25, wherein the sensors comprise fiber optic sensors.27. A method for detecting particle in a fluid within a conduit using aflow meter coupled to the conduit, comprising in order: (a) ceasing theflow of fluid through the conduit; (b) directionally detecting acousticdisturbances within the fluid above the meter at a first time andassessing a first power of the acoustic disturbances; and (c)directionally detecting acoustic disturbances within the fluid above themeter at a second time and assessing a second power of the acousticdisturbances, wherein the second power is greater than the first power.28. The method of claim 27, wherein directionally detecting the acousticdisturbances comprises the use of a kω data set.
 29. The method of claim28, wherein the first and second powers in steps (b) and (c) areassessed along a ridge of the data set.
 30. The method of claim 29,wherein the acoustic disturbances lie along the ridge.
 31. The method ofclaim 27, wherein the acoustic disturbances travel at the speed of soundin the fluid.
 32. The method of claim 27, wherein the flow metercomprises at least two sensors.
 33. The method of claim 32, wherein thesensors are coupled to the outside of the conduit.
 34. The method ofclaim 33, wherein the sensors comprise fiber optic sensors.
 35. A methodfor detecting particle in a fluid within a conduit using a flow metercoupled to the conduit, comprising in order: (a) ceasing the flow offluid through the conduit; (b) directionally detecting acousticdisturbances within the fluid below the meter at a first time andassessing a first power of the acoustic disturbances; and (c)directionally detecting acoustic disturbances within the fluid below themeter at a second time and assessing a second power of the acousticdisturbances, wherein the second power is less than the first power. 36.The method of claim 35, wherein directionally detecting the acousticdisturbances comprises the use of a kω data set.
 37. The method of claim36, wherein the first and second powers in steps (b) and (c) areassessed along a ridge of the data set.
 38. The method of claim 37,wherein the acoustic disturbances lie along the ridge.
 39. The method ofclaim 35, wherein the acoustic disturbances travel at the speed of soundin the fluid.
 40. The method of claim 35, wherein the flow metercomprises at least two sensors.
 41. The method of claim 40, wherein thesensors are coupled to the outside of the conduit.
 42. The method ofclaim 41, wherein the sensors comprise fiber optic sensors.